Questioning the effectiveness of antidepressants

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About a month ago, a spate of news articles popped up with the bold headline, “Prozac doesn’t work,” written in response to a scholarly article from earlier this year that throws doubt on the efficacy of a class of anti-depressant medications (the selective serotonin reuptake inhibitors, or SSRIs), of which Prozac is a member. Aside from the newspaper and magazine responses, the article’s findings set off a rash of posts in the blogosphere and an impassioned, if quiet, debate.

The article in question took the form of a large review, or meta-analysis, of all of the available studies conducted to test the efficacy of SSRIs such as Prozac and Effexor, including some analyses that were not published by the drug companies that conducted them. This article’s analysis was groundbreaking in that it is the largest meta-analysis of its kind ever done for SSRI studies. After pooling all of the data and comparing the efficacies found between studies, the authors concluded that all but the most severely depressed patients given the drugs did not show significant reductions in their depressive symptoms compared to those given placebos.

Of course, anybody who regularly reads science reporting in newspapers or weblogs knows better than to take a statement as unambiguous as “Prozac doesn’t work” without a grain or two of salt. Mainstream scientific articles are filtered through numerous rounds of editing, summarizing, and interpreting in order to be squeezed into a digestible pill the average reader can swallow. Although this conciseness is the beauty of journalism, it means that by necessity much of the complexity — and the subtlety — of the data has been lost. After all, 40 million people have been prescribed Prozac, and I bet a lot of them would be surprised to hear anybody tell them it doesn’t work at all.

The proviso here is that controlled medication studies for psychiatric illnesses are very, very difficult to conduct. Theoretically, you’d want to have a group of depressed people and then another, non-depressed control group, but in reality, constructing “pure” samples is near impossible.

For one, people who volunteer for medication research studies tend to be in lower socio-economic brackets, and tend to comprise the same population that suffers from numerous mental illnesses. These conditions should exclude a number of volunteer patients, but here we encounter the second big problem — screening volunteers relies upon the diagnostic interview. That is, you have to ask a volunteer about his or her symptoms and trust that he or she is telling you the truth, notwithstanding the (sometimes significant) amount of money you’re implicitly offering him or her for enrolling in your study. So, many research subjects lie, meaning that most “control” groups in these experiments are anything but — and researchers have no way of knowing.

And finally, depression so frequently co-occurs with other illnesses, psychiatric and otherwise, that it becomes nearly impossible to have a “pure depression” group — and such other illnesses can significantly impact patients' responses to psychiatric medication, thus obfuscating the results of the study.

Given the difficulties inherent in putting together a subject population, it becomes clear that the subjects easiest to cast are the ones depressed to the exclusion of anything else — meaning, most likely, the subset comprised of the most severely depressed. And this is, coincidentally, the group that the study authors found showed the greatest response to medication. Coincidence?

All that said, this was still a groundbreaking study. Its conclusions convey a surprising message contrary to the conventional wisdom prevalent among research scientists, psychiatrists, and general practitioners (GPs) everywhere. Further, it underscores a misunderstanding of mental illness that is prevalent in society and rooted in an out-of-date scientific viewpoint.

For a few decades, the prevalent view of depression among scientists was something called the “neurotransmitter hypothesis,” which held that the disease was caused by low levels of serotonin and related neurotransmitters. This is where the oft-cited “chemical imbalance” idea came from. But a large body of research has changed this view; nowadays, depression is seen as a more complex process involving social, cognitive, and biological processes in conjunction. This is borne out by data showing that, for many depressed patients, the right kind of therapy is just as effective as medication, if not more so. Further, many depressed patients don’t respond to medicinal therapy at all, and others respond while on the medication but relapse as soon as they’re off of it again.

Inasmuch as the biological aspect of depression involves the serotonin system in the brain, SSRIs are a great treatment, particularly when combined with other forms of therapy. Anti-depressants can throw a kink in the downward spiral of depression, giving a person the opportunity to realign their thinking and get themselves back on track. But these days, perhaps encouraged by pharmaceutical companies or maybe just a cultural lock in our thinking, GPs and psychiatrists prescribe antidepressants with impunity, thus ignoring all of the other aspects of the disease — a person’s relationships, life events, thoughts and feelings — all of the things that make them a person. This exemplifies the American obsession with throwing quick fixes at problems.

SSRIs might not be a great treatment option for people who are not severely depressed. For those people, lifestyle changes, cognitive-behavioral therapy, and other psychosocial adjustments are more effective and cheaper than pills. Just like there is no pill to cure obesity, there is no pill to cure depression. Pharmaceutical companies, and the American government, would be better off investing in research on psychotherapy.

Ceci Westbrook (cwestbro@) is an undergraduate research fellow at Western Psychiatric Institute. She knows more about the neuroscience of emotion than you do, so you should probably listen to her.